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# DrugRNA Dataset
This repository contains the RNA-small molecule interaction prediction dataset used in the paper "LLM Agents Enable RNA–Small Molecule Interaction Prediction at Performance Comparable to Human-Designed Models".
## Dataset Description
The dataset is derived from the RNAInter repository and contains experimentally validated RNA-compound interactions. It includes 45,049 RNA–compound pairs spanning 3,258 unique RNAs and 345 unique compounds, with a 1:4 positive/negative ratio.
## Data Splits
The dataset is organized into three evaluation scenarios:
### 1. In-Distribution Split (`in_distribution/`)
- **Purpose**: Standard 80/10/10 train/validation/test split for head-to-head performance comparison
- **Characteristics**: Complete entity overlap, testing interpolation within known molecular space
- **Files**:
- `train_text.csv` (36,040 samples, 20.0% positive)
- `val_text.csv` (4,504 samples, 19.8% positive)
- `test_text.csv` (4,505 samples, 20.2% positive)
- **Total**: 45,049 samples with 3,258 unique RNAs and 345 unique compounds
### 2. Full Out-of-Domain Split (`full_ood/`)
- **Purpose**: Cold-start prediction with entirely novel entities
- **Characteristics**: Zero overlap for both RNAs and compounds between training and test sets
- **Files**:
- `train_text.csv` (21,794 samples, 18.4% positive)
- `val_text.csv` (1,081 samples, 22.1% positive)
- `test_text.csv` (1,020 samples, 24.2% positive)
- `DATASET_REPORT.md` (detailed statistics and construction methodology)
- **Total**: 23,895 samples with 3,142 unique RNAs and 363 unique compounds
### 3. Compound Out-of-Domain Split (`compound_ood/`)
- **Purpose**: Virtual screening of novel compounds against known RNA targets
- **Characteristics**: Zero compound overlap, complete RNA reuse (86% of training RNAs appear in test)
- **Files**:
- `train_text.csv` (31,576 samples, 21.0% positive)
- `val_text.csv` (6,694 samples, 20.1% positive)
- `test_text.csv` (6,779 samples, 15.2% positive)
- `DATASET_REPORT.md` (detailed statistics and construction methodology)
- **Total**: 45,049 samples with 3,258 unique RNAs and 345 unique compounds
## Data Format
Each CSV file contains the following columns:
- `rna_id`: RNA identifier
- `compound_id`: Compound identifier (PubChem CID)
- `rna_sequence`: RNA nucleotide sequence (A, U, G, C)
- `compound_smiles`: SMILES string representation of the compound
- `label`: Binary interaction label (1 = interaction, 0 = no interaction)
## Scripts
The `scripts/` folder contains:
- `create_disjoint_splits.py`: Script used to generate the out-of-domain splits with strict entity disjointness
## Data Sources
- **RNAs**: Mapped from NCBI, Ensembl, miRBase, and circBase
- **Compounds**: Mapped from PubChem
- **Interactions**: Curated from RNAInter repository with experimental evidence
## Citation
If you use this dataset in your research, please cite:
```bibtex
@article{drugrna2025,
title={LLM Agents Enable RNA–Small Molecule Interaction Prediction at Performance Comparable to Human-Designed Models},
author={...},
journal={...},
year={2025}
}
```
## License
This dataset is provided for research purposes. Please refer to the original data sources for specific licensing information.
## Contact
For questions or issues, please open an issue on the GitHub repository or contact the authors.
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